1. Field of the Invention
The present invention relates to an object detection device, an object detection method and an object detection program for detecting a specific object, such as an eye, from an input image, such as a face image.
2. Description of the Related Art
In recent years, image processing devices are used that detect an eye image from a face image of a driver, which is taken with an on-board camera, and perform various types of processing, such as detecting the gaze direction of the driver, based on the eye image.
As a technique for detecting an eye from a face image, there is a known technique using a plurality of classifiers which are generated and prepared through a learning process using a number of sample images of a predetermined size showing an eye. The classifiers are assigned with different positions on an image to be discriminated, so that each classifier calculates a value that represents a probability of the image to be discriminated being an eye image based on pixel values at the assigned position. Then, partial images of a face image are sequentially cut out to determine whether or not each partial image is an eye image using the classifiers.
However, in the case where the driver wears eyeglasses or sunglasses, sun light or illumination is reflected at the lenses or the frame of the glasses and the reflected light may be captured in the face image, which may hinder the eye image detection from the face image. In order to address this problem, Japanese Unexamined Patent Publication No. 2002-269545 (hereinafter, Patent Document 1) proposes a technique to improve accuracy of eye detection, which involves detecting, from a face image, all the pixels which have a luminance value higher than a predetermined value, substituting the pixel value of each detected pixel with an average color of neighboring pixels to generate a processed image from which high luminance portions have been removed, and detecting an eye from the processed image.
With the technique of Patent Document 1, however, it is necessary to perform, in advance on an image of interest of the detection, the image correction process, such as detecting the high luminance pixels, obtaining the pixel values of the neighboring pixels of each detected pixel and calculating the average value thereof, and substituting the pixel value of each pixel with the calculated average value. Such an image correction process takes time, resulting in low processing speed. This is particularly problematic when the eye detection is performed sequentially on successive images taken with a monitoring camera, or the like. Further, even when such an image correction process is performed, the process may not necessarily be appropriate or sufficient.